NYC Tract Plots

nyc_tracts_acs_sf <- read_rds(here("data", "clean", "nyc_tracts_acs_sf.rds"))

nyc_renter_pct_map <- ggplot(nyc_tracts_acs_sf) +
  aes(fill = renter_pctE) +
  geom_sf(color = "white", size = 0.05) +
  scale_fill_viridis_b(labels = scales::percent) +
  theme_void() +
  theme(legend.position = c(0.1, .75)) +
  labs(
    title = "Renter Share of Units",
    subtitle = "New York City, Census Tracts, 2014-2018",
    fill = NULL,
    caption = "Sources: American Community Survey (2014-2018)"
  )

ggsave(here("img", "nyc_renter_pct_map.png"), nyc_renter_pct_map, width = 6, height = 6)

nyc_hh_inc_map <- ggplot(nyc_tracts_acs_sf) +
  aes(fill = hh_inc_medE) +
  geom_sf(color = "white", size = 0.05) +
  scale_fill_viridis_b(labels = scales::label_number_si()) +
  theme_mspp_map() +
  theme(legend.position = c(0.1, .75)) +
  labs(
    title = "Median Household Income",
    subtitle = "New York City, Census Tracts, 2014-2018",
    fill = NULL,
    caption = "Sources: American Community Survey (2014-2018)"
  )

ggsave(here("img", "nyc_hh_inc_map.png"), nyc_hh_inc_map, width = 6, height = 6)

library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

p <- ggplot(nyc_tracts_acs_sf) +
  aes(x = rent_burden_medE, y = hh_inc_medE, color = boroname) +
  geom_point()

ggplotly(p)

p <- ggplot(nyc_tracts_acs_sf) +
  aes(x = rent_burden_medE, y = hh_inc_medE) +
  geom_point() +
  facet_wrap(~boroname)

ggplotly(p)

## Warning: `group_by_()` is deprecated as of dplyr 0.7.0.
## Please use `group_by()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.

Interactive Maps in R with Leaflet

Leaflet is a popular javascript web mapping framework, and there is a leaflet R package that allows you to create interactive maps directly from sf dataframes that we have been using.

library(leaflet)
library(leaflet.mapboxgl) # remotes::install_github("rstudio/leaflet.mapboxgl")

# If you want to create custom basemaps and use those, you'll need a token, but
# we'll be using preexisting ones from mapbox so we can set this to NA

options(mapbox.accessToken = "pk.eyJ1IjoiYXVzdGVuc2VuIiwiYSI6ImNqa2lnOXJhYTAwOHgzcnM2bDk1b2wyMzQifQ.4TZ4jUC2_LDICORTKVR3yg")

# This creates a function that takes a column of values and categorizes them an
# matches it to a color in the way that leaflet requires
hh_inc_pal <- colorBin(viridisLite::viridis(5), nyc_tracts_acs_sf$hh_inc_medE, n=5)

nyc_map_leaflet <- nyc_tracts_acs_sf %>% 
  # You should always re-project your data into lat/lon 4326 CRS
  st_transform(4326) %>% 
  leaflet() %>% 
  # This option doesn't require a token
  # addProviderTiles(providers$CartoDB.Positron) %>% 
  # This option requires a token - you can use mine to test it out today, but
  # then need to sig up for your own (free) token
  addMapboxGL(style = "mapbox://styles/mapbox/light-v9") %>%
  # For point data use addCircleMarkers()
  addPolygons(
    # In leaflet to refer to columns in your dataframe in arguments use the ~ at the beginning
    fillColor = ~hh_inc_pal(hh_inc_medE),
    fillOpacity = 0.7,
    color = "white",
    weight = 0.5,
    # You can use html to format this any way you want. Here we use str_glue()
    # to insert values from our columns and use R formatting funcitons.
    # Everything inside the {} gets evaluated as R code
    popup = ~str_glue("<strong>Median Household Income (2014-2018)</strong><br>
                      {scales::dollar(hh_inc_medE)} (±{scales::comma(hh_inc_medM, 1)})")
  ) %>% 
  addLegend(
    position = "topleft", 
    pal = hh_inc_pal, 
    values = ~hh_inc_medE, 
    labFormat = labelFormat(prefix = "$"),
    title = "Median Household Income<br>by Census Tract (2014-2018)"
  )

nyc_map_leaflet

If you print the result of the leaflet functions the interactive map can be included directly in the final Rmarkdown document, but this only wors with the html_output option. You can also use the htmlwidgets package to export our map to an HTML file. You can even then host this as mini website using GitHub (ask me for examples/help if you want to do this, it’s not that hard).

htmlwidgets::saveWidget(nyc_map_leaflet, here("docs", "nyc-map-leaflet.html"), selfcontained = TRUE)